SOTAVerified

Transfer Learning

Transfer Learning is a machine learning technique where a model trained on one task is re-purposed and fine-tuned for a related, but different task. The idea behind transfer learning is to leverage the knowledge learned from a pre-trained model to solve a new, but related problem. This can be useful in situations where there is limited data available to train a new model from scratch, or when the new task is similar enough to the original task that the pre-trained model can be adapted to the new problem with only minor modifications.

( Image credit: Subodh Malgonde )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3951–4000 of 10307 papers

TitleStatusHype
Comparison of fine-tuning strategies for transfer learning in medical image classification—0
A Compare-Aggregate Model with Latent Clustering for Answer Selection—0
FedDistill: Global Model Distillation for Local Model De-Biasing in Non-IID Federated Learning—0
Evaluation of Federated Learning in Phishing Email Detection—0
Federated Adversarial Domain Adaptation—0
Federated and Transfer Learning: A Survey on Adversaries and Defense Mechanisms—0
Federated and Transfer Learning for Cancer Detection Based on Image Analysis—0
Federated Automatic Latent Variable Selection in Multi-output Gaussian Processes—0
Decoupled classifiers for fair and efficient machine learning—0
Comparison of semi-supervised learning methods for High Content Screening quality control—0
Comparison of Transfer Learning based Additive Manufacturing Models via A Case Study—0
Decoupled Box Proposal and Featurization with Ultrafine-Grained Semantic Labels Improve Image Captioning and Visual Question Answering—0
Federated Cross-Domain Click-Through Rate Prediction With Large Language Model Augmentation—0
Federated deep transfer learning for EEG decoding using multiple BCI tasks—0
Federated Distillation: A Survey—0
A Multimodal German Dataset for Automatic Lip Reading Systems and Transfer Learning—0
Complete Multilingual Neural Machine Translation—0
Federated Domain-Specific Knowledge Transfer on Large Language Models Using Synthetic Data—0
Federated Graph Learning for Cross-Domain Recommendation—0
Federated Graph Learning with Graphless Clients—0
Federated Imitation Learning: A Novel Framework for Cloud Robotic Systems with Heterogeneous Sensor Data—0
Federated Imitation Learning: A Privacy Considered Imitation Learning Framework for Cloud Robotic Systems with Heterogeneous Sensor Data—0
Using LLMs to Establish Implicit User Sentiment of Software Desirability—0
Federated learning: Applications, challenges and future directions—0
Federated Learning for Autoencoder-based Condition Monitoring in the Industrial Internet of Things—0
Federated Learning for Emoji Prediction in a Mobile Keyboard—0
Decomposition-Based Transfer Distance Metric Learning for Image Classification—0
Federated Learning -- Methods, Applications and beyond—0
Federated Learning Optimization: A Comparative Study of Data and Model Exchange Strategies in Dynamic Networks—0
Federated Learning without Full Labels: A Survey—0
Composing Task-Agnostic Policies with Deep Reinforcement Learning—0
Federated Multi-View Synthesizing for Metaverse—0
Time-Frequency Analysis based Deep Interference Classification for Frequency Hopping System—0
Federated Deep Reinforcement Learning—0
A Multi-media Approach to Cross-lingual Entity Knowledge Transfer—0
Federated Semi-Supervised Domain Adaptation via Knowledge Transfer—0
Compositional Models: Multi-Task Learning and Knowledge Transfer with Modular Networks—0
Federated Transfer Component Analysis Towards Effective VNF Profiling—0
Federated Transfer Learning Aided Interference Classification in GNSS Signals—0
Federated Transfer Learning Based Cooperative Wideband Spectrum Sensing with Model Pruning—0
Decomposed Cross-modal Distillation for RGB-based Temporal Action Detection—0
Decomposable Probability-of-Success Metrics in Algorithmic Search—0
Automated Segmentation and Analysis of Microscopy Images of Laser Powder Bed Fusion Melt Tracks—0
Federated Transfer Learning with Dynamic Gradient Aggregation—0
Adaptive Transfer Learning for Plant Phenotyping—0
Federated Transfer Learning with Task Personalization for Condition Monitoring in Ultrasonic Metal Welding—0
Exploring Semantic Attributes from A Foundation Model for Federated Learning of Disjoint Label Spaces—0
FedGTST: Boosting Global Transferability of Federated Models via Statistics Tuning—0
FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearch—0
G2L: A Geometric Approach for Generating Pseudo-labels that Improve Transfer Learning—0
Show:102550
← PrevPage 80 of 207Next →
All datasetsOffice-Home100 sleep nights of 8 caregiversBanglaLekha Isolated DatasetCOCO70KITTI Object Tracking Evaluation 2012Retinal Fundus MultiDisease Image Dataset (RFMiD)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1APCLIPAccuracy84.2—Unverified
2DFA-ENTAccuracy69.2—Unverified
3DFA-SAFNAccuracy69.1—Unverified
4EasyTLAccuracy63.3—Unverified
5MEDAAccuracy60.3—Unverified
#ModelMetricClaimedVerifiedStatus
1CNN10-20% Mask PSNR3.23—Unverified
#ModelMetricClaimedVerifiedStatus
1Chatterjee, Dutta et al.[1]Accuracy96.12—Unverified
#ModelMetricClaimedVerifiedStatus
1Co-TuningAccuracy85.65—Unverified
#ModelMetricClaimedVerifiedStatus
1Physical AccessEER5.74—Unverified
#ModelMetricClaimedVerifiedStatus
1riadd.aucmediAUROC0.95—Unverified